Exposure-lag response of air temperature on COVID-19 incidence in twelve Italian cities: A meta-analysis

Seasonal variation of Covid-19 incidence and role of land surface and air temperatures: a case study in the west of Iran

.In this study, we assessed the impact of satellite-based Land Surface Temperature (LST) and Air Temperature (AT) on covid-19. First, we spatio-temporally kriged the LST and applied bias correction. The epidemic shape, timing, and size were compared after and before adjusting for the predictors. Given the non-linear behavior of a pandemic, a semi-parametric regression model was used. In addition, the interaction effect between the predictors and season was assessed. Before adjusting for the predictors, the peak happened at the end of hot season. After adjusting, it was attenuated and slightly moved forward. Moreover, the Attributable Fraction (AF) and Peak to Trough Relative (PTR) were % 23 (95% CI; 15, 32) and 1.62 (95%CI; 1.34, 1.97), respectively. We found that temperature might have changed the seasonal variation of covid-19. However, given the large uncertainty after adjusting for the variables, it was hard to provide conclusive evidence in the region we studied.

Investigation of the effects of temperature and relative humidity on the propagation of COVID-19 in different climatic zones

This study aims to evaluate the effects of temperature and relative humidity on the propagation of COVID-19 for indoor heating, ventilation, and air conditioning design and policy development in different climate zones. We proposed a cumulative lag model with two specific parameters of specific average temperature and specific relative humidity to evaluate the impact of temperature and relative humidity on COVID-19 transmission by calculating the relative risk of cumulative effect and the relative risk of lag effect. We considered the temperature and relative humidity corresponding to the relative risk of cumulative effect or the relative risk of lag effect equal to 1 as the thresholds of outbreak. In this paper, we took the overall relative risk of cumulative effect equal to 1 as the thresholds. Data on daily new confirmed cases of COVID-19 since January 1, 2021, to December 31, 2021, for three sites in each of four climate zones similar to cold, mild, hot summer and cold winter, and hot summer and warm winter were selected for this study. Temperature and relative humidity had a lagged effect on COVID-19 transmission, with peaking the relative risk of lag effect at a lag of 3-7 days for most regions. All regions had different parameters areas with the relative risk of cumulative effect greater than 1. The overall relative risk of cumulative effect was greater than 1 in all regions when specific relative humidity was higher than 0.4, and when specific average temperature was higher than 0.42. In areas similar to hot summer and cold winter, temperature and the overall relative risk of cumulative effect were highly monotonically positively correlated. In areas similar to hot summer and warm winter, there was a monotonically positive correlation between relative humidity and the overall relative risk of cumulative effect. This study provides targeted recommendations for indoor air and heating, ventilation, and air conditioning system control strategies and outbreak prevention strategies to reduce the risk of COVID-19 transmission. In addition, countries should combine vaccination and non-pharmaceutical control measures, and strict containment policies are beneficial to control another pandemic of COVID-19 and similar viruses.

Short-term exposure to ambient fine particulate pollution aggravates ventilator-associated pneumonia in pediatric intensive care patients undergoing cardiovascular surgeries

BACKGROUND

Ambient air pollutants can be hazardous to human health, especially for vulnerable children. The impact of ambient air pollutant exposure before and during intensive care unit (ICU) stays on the development of ventilator-associated pneumonia (VAP) in critically ill children has not been established. We aimed to determine the correlations between short-term exposures to ambient fine particulate matter (PM_2.5) and VAP in pediatric cardiac surgery patients in the ICU, and explore the effect of delayed exposure.

METHODS

The medical record of 1755 child patients requiring artificial ventilation in the ICU between December 2013 to December 2020, were analyzed. The daily average concentrations of particulate matters (PM_2.5 and PM₁₀), sulfur dioxide (SO₂), and ozone (O₃) were calculated from public data. Interactions between these pollutants and VAP were simulated with the distributed lag non-linear model.

RESULTS

Three hundred forty-eight cases (19.829%) of VAP were identified in this study, while the average concentrations of PM_2.5, PM₁₀, O₃ and SO₂ were 58, 118, 98 and 26 μg/m³, respectively. Exposure to increased levels of PM_2.5 two days prior (lag 2-day) to VAP diagnosis is significantly correlated with an enhanced risk for VAP development. Even a slight increase of 10 μg/m³ in PM_2.5 can translate to a 5.4% increase in VAP incidence (95% CI: 1.4%-9.5%) while the VAP incidence increased to 11.1% (95%CI: 4.5-19.5%) when PM_2.5 concentration is well below the National Ambient Air Quality standard (NAAQS) of 50 μg/m³. The association was more pronounced in those aged below 3-months, with low body mass index or suffered from pulmonary arterial hypertension.

CONCLUSION

Short-term PM_2.5 exposure is a significant risk for development of VAP in pediatric patients. This risk is present even with PM_2.5 levels below the NAAQS. Ambient PM_2.5 may represent a previously unrecognized risk factor for pneumonia and the current environmental pollution standards need to be reevaluated to consider susceptible populations.

TRIAL REGISTRATION

The trial was registered with the National Clinical Trial Center: The correlation between ambient air pollution and the complications in ICU underwent cardiac surgery.

TRIAL REGISTRATION NUMBER

ChiCTR2000030507. Date of registration: March 5, 2020. URL of trial registry record: http://www.chictr.org.cn/index.aspx .

Analysis of the effect of temperature on tuberculosis incidence by distributed lag non-linear model in Kashgar city, China

The aim of this study was to explore the effect of temperature on tuberculosis (TB) incidence using the distributed lag non-linear model (DLNM) from 2017 to 2021 in Kashgar city, the region with higher TB incidence than national levels, and assist public health prevention and control measures. From January 2017 to December 2021, a total of 8730 cases of TB were reported, with the higher incidence of male than that of female. When temperature was below 1 °C, it was significantly correlated with TB incidence compared to the median observed temperature (15 °C) at lag 7, 14, and 21, and lower temperatures showed larger RR (relative risk) values. High temperature produced a protective effect on TB transmission, and higher temperature from 16 to 31 °C has lower RR. In discussion stratified by gender, the maximum RRs were achieved for both male group and female group at - 15 °C with lag 21, reporting 4.28 and 2.02, respectively. At high temperature (higher than 20 °C), the RR value of developing TB for female group was significantly larger than 1. In discussion stratified by age, the maximum RRs were achieved for all age groups (≤ 35, 36-64, ≥ 65) at - 15 °C with lag 21, reporting 3.20, 2.07, and 3.45, respectively. When the temperature was higher than 20 °C, the RR of the 36-64-year-old group and the ≥ 65-year-old group was significantly larger than 1 at lag 21, while significantly smaller than 1 for cumulative RR at lag 21, reporting 0.11, 95% confidence interval (CI) (0.01, 0.83) and 0.06, 95% CI (0.01, 0.44), respectively. In conclusion, low temperature, especially in extreme level, acts as a high-risk factor inducing TB transmission in Kashgar city. Males exhibit a significantly higher RR of developing TB at low temperature than female, as well as the elderly group in contrast to the young or middle-aged groups. High temperature has a protective effect on TB transmission in the total population, but female and middle-aged and elderly groups are also required to be alert to the delayed RR induced by it.

The association of COVID-19 incidence with temperature, humidity, and UV radiation - A global multi-city analysis

BACKGROUND AND AIM

The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally.

METHODS

We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone.

RESULTS

We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries.

CONCLUSION

Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission.

Using a novel two-stage strategy to characterize the spatial distribution of associations between temperature and COVID-19: A case study in the continental United States

BACKGROUND

Numerous studies have studied the association between daily average temperature (DAT) and daily COVID-19 confirmed cases, which show considerable heterogeneity, even opposite results, among different regions. Such heterogeneity suggests that characterizing the association on a large area scale would ignore the local variation, even obtain false results in some local regions. So, characterizing the spatial distribution of heterogeneous DAT-COVID-19 associations and exploring the causes plays an important role on making temperature-related region-specific intervention measures and early-warning systems.

METHODS

Aiming to characterize the spatial distribution of associations between DAT and COVID-19 confirmed cases in the continental United States, we proposed a novel two-stage strategy. In the first stage, we used the common stratified distributed lag nonlinear model to obtain the rough state-specific associations. In the second stage, conditional autoregression was used to spatially smooth the rough estimations. Furtherly, based on the idea, two modified strategies were used to investigate the time-varying associations and the modification effects derived from the vaccination campaign.

RESULTS

Around one-third of states exhibit no significant association between DAT and daily confirmed COVID-19 cases. Most of the remaining states present a low risk at low DAT and a high risk at high DAT, but several states present opposite associations. The average association curve presents a 'S' shape with positive association between -8 - 18 °C and keeping flat out of the range. An increased vaccination coverage rate will increase the risk when DAT < 12 °C, but slightly affect the risk when DAT > 12 °C.

CONCLUSION

A considerable spatial heterogeneity of DAT-COVID-19 associations exists in America and the average association curve presents a 'S' shape. The vaccination campaign significantly modifies the association when DAT is low, but only make a slight modification when DAT is high.

Optimization of the Beijing Economy-Energy-Emissions System 2021-2035: A Scenario Simulation Analysis Based on a System Dynamics Model

This paper constructs an Economy-Energy-Emissions (3E) System Dynamics Model using the megacity of Beijing, China, as an example, to estimate the effects of different policy scenarios (including three single-policy scenarios and four combined-policy scenarios) on the core variables of Beijing's 3E system from 2021 to 2035. The results suggest two main points. (1) Following the current development trend, the proportion of the GDP represented by the added value of advanced high-precision industries (Gao Jing Jian in Chinese) will only be 43% in 2035, implying a limited role in promoting economic growth. Despite effective control of total energy consumption, fossil energy's share of total consumption will reach 57% by 2035, hindering the process of making the energy consumption structure cleaner and leading to failure to achieve the targeted inflection point in CO2 emissions by 2025. PM2.5 control shows some successful results and will decrease to 19 μg/m3 in 2035. However, a gap compared to other world-class cities remains. (2) The implementation of a single policy for either industrial structure optimization, energy structure transformation, or emissions control cannot simultaneously meet the goal of high-quality coordinated development of Beijing's 3E system, whereas the comprehensive implementation of policies in all three dimensions is demonstrably effective.